Spatial Association Patterns with Cultural and Behaviour with the Situations of COVID-19

Yotha, N.,¹ Phimha, S.,¹ Prasit, N.,¹* Senahad, N.,¹ Sirikarn, P.¹ and Nonthamat, A.²

¹Faculty of Public Health, Khon Kaen University, Khon Kaen, Thailand

E-mail: Nakapr@kku.ac.th*

²Bangkok Hospital Khonkaen, Khon Kaen University, Khon Kaen, Thailand

*Corresponding Author

Abstract

This study is a cross-sectional study. The study of spatial association patterns and the influences on the Coronavirus Disease 2019 (COVID-19) epidemic situation in Thailand was determined using secondary data from the COVID-19 interactive dashboard, Department of Disease Control, Ministry of Public Health, between January 1st, 2020, and December 31st, 2021. Moran’s I, Local Indicators of Spatial Association (LISA), and Spatial Regression was applied for statistical analysis. In the epidemic situation of COVID-19, the highest of 11,512.65 per one hundred thousand population, and the spatial association between the nighttime light average, the prevalence of smokers in Thailand, the proportion of population per village health volunteer, and the proportion of population per health care center with the epidemic situation of COVID-19 has Moran’s I = 0.309, 0.396, 0.081 and 0.424, respectively. From the Spatial Lag Model (SLM), a factor that has a spatial association with the epidemic situation of COVID-19 is the nighttime light average, the prevalence of smokers in Thailand, and the proportion of population per healthcare center, which can predict the epidemic situation of COVID-19 by 47.8 percent (R²=0.478). The growth factor of a large city is an important factor for population density which is a major cause of spread of the coronavirus easily. Moreover, smoking behavior has encouraged the epidemic to spread rapidly. The situation is serious as the number of hospitals is not enough to support the treatment and screening of patients to cover the entire population of Thailand. Therefore, it is urgent that the government plan to mitigate the situation with maximum efficiency by having COVID-19 centers and increase the number of beds and facilities.

Keywords: Coronavirus Disease 2019, COVID-19, Spatial analysis, nighttime light average, Smoking behavior, village health volunteer, proportion of population per healthcare center

1.Introduction

The diffusion of the pandemic of Coronavirus Disease 2019 into various areas in Thailand occurred due to a lack of readiness for new infectious diseases and also a huge number of emergency calls, which makes responding very difficult. Thailand’s economy is seriously affected by the rising number of Coronavirus Disease 2019 infections [1]. The pandemic situations of Coronavirus Disease 2019 in other countries are also very serious, such as Singapore 1,879,806 cases, Iraq 2,459,178 cases, Malaysia 4,821,864 cases, Indonesia 6,415,328 cases, China 7,230,178, and Vietnam 11,463,404 cases [2]. Due to cultural, traditional and religious factors, most of these countries received high damage from this pandemic from their risky lifestyle limitation, especially while “distancing” from the Coronavirus Disease 2019. Spatial factor is also a big factor to overview of how to fix the pandemic situation in terms of planning and controlling [3] and [4].

Thailand has opened the Center for the Administration of the Covid Situation due to the outbreak of the Communicable Disease Coronavirus 2019 (COVID-19) for public health emergency response, also administratively directing, controlling, and monitoring the situation. Thailand has a cumulative patient population of 2,223,435 individuals from the first patient until December 31st, 2021. It recorded the total cured 2,168,494 individuals, and deceased 21,698 individuals, which is 0.98 percent [5]. Although Thailand had policy measures to deal with the spread of the Coronavirus Disease 2019 at that time [6] and [7], the number of infected people tended to be higher.

5. Discussions

Nighttime Light is one of spatial factor which showing the growth of economy and provincial expansion in Thailand, and also changing of civilization, immigration, which reflex to citizen activities, traditions, cultures, economy growth, and cities expansion. The result show in form of the average of light intensity in the nighttime and county map [12]. From the previous result, which according to Thailand situations, clearly present that growth economy cities are more pandemic than the middle-small economy cities [13], which make the pandemic control of Coronavirus Disease 2019 are not successfully, made it turn to be the one factor to make policy draft Distancing, Mask wearing, Hand washing, Testing and Thai Chana to adjust social situations, especially social office, citizens necessary to work for their lives, refer to life quality, struggling for a living [1] [21] and [22]. Except from the topic of the light, health consciousness building is also main factor too, especially smoking behavior, and Thailand is face to this problem to fix smoking behavior of Thai people [23]. Smoking is directly cause harmful to lounge and respiratory tract, which make worse to resist the Coronavirus Disease 2019 and other chronic diseases [14] moreover, smoking is not only harm the people who smoke, but it also harms other people and social in from of second-hand smoking, the cigarette’s smoke can cause skin irritation and harm lounge, decrease bodies immunity and respiratory tract, the damage is highly rising if the smoker is pandemic from Coronavirus Disease 2019 [24] and [25]. The next factor is healthcare, this factor is necessary to improve for preparing for emergency situations in Thailand. Volunteer public health in villages are in the big role to serve medical services to people in communities, and Thailand is the only one country which have the volunteer public health in villages [26] between the pandemic of Coronavirus Disease 2019, they activate for support medical personal [27]. However, the high population density in the growth cities makes citizens immigrate into big towns, which causes the problem of reaching medical services because the number of citizens is too much to handle for volunteer public health (Figure 4(d)). Especially in the pandemic situation of Coronavirus Disease 2019, which make volunteer public health get a big role in "volunteer public health proactive" in term of screen patients, tracking patients in community, check the medical supplements for protect Coronavirus Disease 2019 in each area (Ministry of Public Health, 2020). Therefore, it’s necessary that the government give attention to this role, which is like an outpost position. Government agencies should adjust volunteer public health numbers to suit the numbers of people in each village [28]. In other hand, managing medical personal to take respond at hospital is important too. From the study, more hospital in province is more potential to screen people whom pandemic from Coronavirus Disease 2019 and able to cure them in time [29] and [30]. Therefore, it’s necessary that government agency should give attention to develop hospital and adjust medical personal in each location enough to take care overall people, including with facing with pandemic COVID-19 which is a good chance to make new level of public health and widespread better healthcare service, and preparing for chronic disease in the future.

In this study, spatial regression statistics were used to find the best model to predict the spread of the Coronavirus Disease 2019 during the years 2020–2021, which was observed from the high R-value in the study of the best model, the best of each model. They consisted of the OLS model (no statistical assumption was involved in model control), the SLM model (peripheral area to calculate model variance), and the SEM model (the difference coefficient of each area is also calculated), and from this study, the SLM model is the best model. The factors that affect it include the average amount of light at night. The prevalence of smoking behavior and the population accountability of the healthcare unit can predict the spread of the novel Coronavirus Disease 2019 during 2020-2021 for 47.8% of the people in the above study. It is consistent with past studies, which found that the average amount of light at night indicates economic growth and urbanity of each province. The media shows the growth of that province, which leads to population density in provinces with high economic growth and causes the risk of It is easier to spread the Coronavirus Disease 2019 than in dense provinces. Underpopulation in terms of maintaining social distancing measures as a result of crowded population density, making it difficult to control collectively in terms of controlling measures and laws for disease prevention and control it's difficult because of the difference. The presence of urban communities increases the risk of controlling the spread of the coronavirus disease in 2019 is consistent with the findings of previous research studies [12] and [31], which, based on the above-mentioned population density results, indicate that another consequent factor is population density and urbanization influencing the global spread of health risk behaviors, particularly smoking behavior. In addition, smoking behavior is a threat in spreading the virus. Coronavirus Disease 2019 enters the lungs from smoking cigarettes and smoking also spreads the virus widely in the form of second-hand cigarettes, which will affect people’s surroundings to be infected with Coronavirus Disease 2019 unknowingly corresponds to the population density of large cities. In addition, smoking behavior is also a problem for Thailand in proper control of smoking measures, especially the control of smoking areas, leading to the highest risk. According to the findings of previous research studies [24] and [32], the spread of the Coronavirus Disease in 2019 will be concentrated in large cities, as well as treatment, prevention, and promotion of healthy behaviors. Another important factor in preventing the spread of the coronavirus disease in 2019 is the role of the medical service in the spread situation. of various epidemics, which is in one direction of the nighttime average. It conveys the density of the population of each province, which is overcrowded and may not be enough for the hospital service unit to provide appropriate health services, including promotion, prevention, and control of the disease. Efficiently as a result, the population will be unable to begin early treatment and disease control in those infected with the coronavirus disease in 2019. Consistent with the results of past research studies [22] [30] and [33]. The three factors mentioned above are consistent in the context of the growth of being a big city that affects the use of appropriate measures and laws to regulate the behavior of individuals to prevent the 2019 epidemic, so it is absolutely necessary that the relevant agencies will recognize the importance of developing a policy that is tailored to each province's unique culture, traditions, and ways of life, and that each province's economic growth will be prioritized.

Depending on the results of this research, governments, and related agencies should revise and adopt policies that promote COVID-19 prevention and medical and public health development. Particularly, regulations that are consistent with addressing and preventing unhealthy situations promote serious and transparent preventative activities. Including a strategy to encourage the establishment of village health volunteer leaders with health knowledge and the ability to adapt their conduct to the era of globalization. That requires technology to be utilized in the medical service system that is current and capable of successfully disseminating health news, as well as promoting and growing the health system's potential. Sufficient medical facilities and medical personnel are needed for potential future emergency scenarios. Therefore, it is essential to prioritize the design of policies based on the integration that fosters inclusive learning and implementation in all areas. To execute the policy in the public sector, the private sector and both sectors can collaborate. This will result in sustained growth across all sectors for Thailand's benefit in a sustainable way.

6. Conclusion

Average nighttime light indicates economic expansion. The population density of each city contributes to spread of coronavirus disease 2019 and also indicates population activities and urban dynamics. The infection and fatality rates of the new coronavirus disease 2019 are greater in high-density metropolitan regions compared to locations with an averagely low concentration of nighttime light. Individuals who engage in smoking pose a risk to themselves as well as to others and to society. in the form of passive smoking. There will be secretions coupled with smoke or vapor dispersion, which will have an impact on others in the vicinity. In crowded or poorly ventilated settings, the COVID-19 infection may spread far from the exhalation of cigarette smoke which increases the rate of disease transmission and the risk of virus infection. especially in regions with sufficient hospitals. This will enable screening and treatment for COVID-19 in a timely manner before the symptoms become life-threateningly severe. Therefore, diverse government initiatives must be supported, integrating all sectors in the fight against the disease to increase public understanding of rigorous self-defense. In order to prevent the spread of disease, the creation of medical facilities that are efficient and adequate for the population and the promotion of non-smoking in public spaces are important aspects of society to provide emergency assistance for emerging illnesses in a thorough and effective manner. This will result in ongoing progress in every sector for Thailand's long-term prosperity.

Acknowledgments

The authors would like to express their sincere appreciation to Department of Disease Control, Ministry of Public Health, Thailand for dataset. Special thanks to the Faculty of Public Health, Khon Kaen University, Khon Kaen University, Thailand for the support.

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